Exoskeletons are structures of rigid links mounted on a body that restore, rehabilitate, or enhance the human motor function. Effective use of exoskeletons for restoration or enhancement of motor function has potentially widespread applications in areas such as rehabilitation robotics, injury prevention, performance enhancement, and in helping humans with disabilities or compromised neuromuscular function. However, conventional exoskeleton systems are at an early stage of development, with some progress having been made in the field of rehabilitation. See Saso Jezernik, Gery Colombo, Thierry Keller, Hansruedi Frueh, and Manfred Morari, Robotic orthosis Lokomat: A rehabilitation and research tool, Neuromodulation, 6(2): 108-115, 2003, which is incorporated by reference herein in its entirety. Conventional techniques for human-exoskeleton control tend to rely on unreliable calculation of first and second order time derivatives of noisy generalized coordinates. Conventional exoskeleton controllers are also susceptible to uncertainties in measurement of body parameters such as body segment mass, center of mass, and length.
The complexity of the central nervous system (CNS) control and the interface between voluntary control and external artificial control presents significant obstacles to the control of a human-exoskeleton system. When humans interact with an external force field such as an exoskeleton, the central nervous system needs to learn an internal model of the force field and interaction with the force field. See R. Shadmehr, T. Brashers-Krug, and F. Mussa-Ivaldi, Interference in learning internal models of inverse dynamics in humans, in G. Tesauro, D. S. Touretsky, and T. K. Leen, eds., Advances in Neural Information Processing Systems, chapter 7, pages 1117-1224, MIT Press, 1995, which is incorporated by reference herein in its entirety. Therefore, a major challenge in the design and use of exoskeletons for daily activities relates to the coupled control of a human-exoskeleton system.
Another challenge to designing an exoskeleton controller is that an expected trajectory is not available to the controller because the intended human motion cannot be predicted in advance by an exoskeleton controller. Human motion generally takes place in a dynamic environment and forces that will act on a body are also unpredictable. The inability to predict the intended motion in addition to interaction with uncertain dynamic environments creates a need for online or real-time control of a human-exoskeleton system.
The coupled control of a human-exoskeleton system may lead to mechanical and metabolic inefficiencies if the assist controller is not properly designed. For example, an exoskeleton controller may degrade efficiency for certain tasks in which the natural and passive dynamics of the system help the progression of motion. Efficiencies due to the natural dynamics are evident in human gait motion, which is believed to be a highly efficient motion due to the passive transfer of potential to kinetic energy, with the primary source of energy for hip flexion during the swing phase of gait being generated by gravity effects. An exoskeleton control strategy should be mechanically and metabolically efficient. Accordingly, there is a need to assess the mechanical and metabolic costs associated with an exoskeleton controller and to determine its feasibility in terms of energy efficiency.
For a human-exoskeleton system, there is a need for exoskeleton control strategies that enhance, rehabilitate and restore the human motor function without the errors caused by calculation of higher order derivatives of kinematic data with noise. There is a need for exoskeleton controllers that are compatible with complex voluntary control performed by the central nervous system and that are capable of energy efficient, real-time control.